Primary keyword: occupancy monitoring solution. Stavanger’s city center expanded its WiFi node network and paired it with 3D people-counting sensors to map footfall and movement across streets and plazas. The result: clearer retail insights, better visitor experience, and resilient city operations.
WHY CITY CENTERS NEED PEOPLE FLOW INSIGHT
Footfall is a leading indicator for downtown vitality: staffing, opening hours, events, and safety all benefit when decision-makers can quantify how many people visit, when they come, and where they move. Without reliable data, operators guess—risking under- or over-staffing, queue build-ups, and missed sales.
HOW STAVANGER BUILT A SCALABLE SETUP
Stavanger combined existing WiFi access points with 3D sensors to increase coverage. WiFi adds wide-area presence signals across large spaces; sensors add calibrated accuracy for counting, direction, and dwell near key streets and entries. Together they deliver a practical, GDPR-aware occupancy monitoring solution for public spaces and retailers.
Coverage: More WiFi nodes extend detection across the city center.
Accuracy where it matters: 3D sensors (e.g., from partners like Xovis) deliver precise counts at doors and corridors.
Flexible rollout: If a city already runs enterprise WiFi, visitor analytics can often start with minimal new hardware.
WHAT DATA STAKEHOLDERS SEE
City teams, BIDs, and retailers access dashboards for hour-by-hour traffic, daily and weekly patterns, and event impact. With trendlines and weather/event overlays, planners can test hypotheses, optimize promotion windows, and coordinate street activities with nearby venues.
USE CASES ACROSS THE CITY
Retail & hospitality: Align staffing to peaks, measure conversion alongside POS, and benchmark streets.
Public realm & events: Evaluate programming impact, balance flows between squares, and support safety operations.
Transport touchpoints: Understand spillover from stations and parking to shopping streets.
IMPLEMENTATION & PRIVACY
CountMatters integrates visitor counting sensors and enterprise WiFi within one analytics layer. All processing follows strict GDPR practices with aggregation, retention controls, and opt-out mechanisms. No facial recognition—ever. Data is used to quantify flows and occupancy, not identify individuals.
ROI & OPERATIONAL IMPACT
With dependable traffic baselines, Stavanger can plan seasonal staffing, coordinate campaigns among merchants, and rapidly assess the effects of disruptions or new street designs. Retailers gain visibility into true opportunity, not just transactions—closing the loop between retail footfall analytics and sales outcomes.
ROI
A small uptick in conversion can have outsized impact. See how visitor data changes the math.
Your scenario
Your baseline. Typical retail: 8–12%.
Lift is measured in absolute percentage points (e.g., +2 pp from 10% → 12%).
Currency is auto-detected for display.
+0% % relative lift
What it means:
What it means
Projected revenue uplift (per month)
Additional orders (per month)
Validated in production; typical accuracy 94–98% with on-device anonymization.
FAQ
How accurate is the system?
3D sensors provide high counting accuracy at critical pinch points. WiFi augments coverage to reveal macro-level flows across large zones.
Do we need new hardware?
Often, no. Existing enterprise WiFi can be enabled for analytics, and sensors are added where precision is needed most.
Is it GDPR-compliant?
Yes—data is aggregated and privacy-preserving. No personally identifying information is processed.
What does it cost?
Pricing depends on coverage, number of sensors, and integration scope. We’ll scope a plan that matches your footprint and KPIs.
Real-Time Occupancy Revenue Impact
Retail wait time increases and satisfaction impact
Queues Kill Revenue After 4–5 Minutes
Customer abandonment rates by wait time threshold
Source: Qminder consumer surveys
Wait Times Up; Satisfaction Down
Retail wait time increases and satisfaction impact
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